Detection and Rectification of Distorted Fingerprints

Information Science and Engineering

NATIONAL CONFERENCE on VLSI, COMMUNICATION AND SIGNAL PROCESSING (NCVCS-2017)

The major problem with all fingerprint recognition system is elastic distortion. It is very dangerous in negative recognistion applications, such as deduplication applications. So more importance should be given in negative recognition application. In this paper, we suggested novel algorithms to detect and rectify skin distortion based on a single fingerprint image. Distortion detection is displayed as a two-class categorization problem, for which the registered ridge orientation map and period map of a fingerprint are beneficial as the feature vector and a SVM classifier is trained to act the classification task. Equivalently distortion field estimation is viewed as a regression complication, where the input is a distorted fingerprint and the output is the distortion field. To solve this issue, reference database of various distorted reference fingerprints and corresponding distortion fields is built in the offline stage, and then in the online stage, the closest neighbor of the input fingerprint is organized in the reference database and the corresponding distortion field is used to transform the input fingerprint into a normal fingerprints. Promising results have been obtained on three databases having many distorted fingerprints, namely FVC2004 DB1.

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